Processes can be generally classified into three categories: continuous processes, semi-continuous processes, and batch processes. A continuous process is one which operates on raw materials or feed elements at a continuous rate to produce a continuous stream of product at an output. Examples of continuous processes include petroleum refining processes, vitamin C production processes and certain commodity chemical manufacturing processes. The values of process variables, such as temperature, pressure, flow rate, etc., typically remain the same over time at any location within a continuous process.
A batch process is a process which operates on a limited quantity of raw materials or feed elements as a group and which forces those feed elements through a series of process steps over time to produce an output product at the completion of the process steps. Usually, no new feed elements are introduced into a batch process during operation of the process steps. Examples of batch processes include the manufacture of beer, the manufacture of some pharmaceutical drugs and the production of many specialty chemicals. The values of process variables, such as temperature, pressure, flow rate, etc., typically change over time at one or more locations within a batch process.
A semi-continuous process is a continuous process which has batch process components therein. Typically, a semi-continuous process operates on a continuous supply of raw materials to produce a continuous stream of output product but has a set of, for example, mixers which mix a limited quantity of the materials being processed for a limited time somewhere within the process.
With regard to batch processes (and batch process components of semi-continuous processes) it may be useful to estimate a future state of a batch process based on past or current values of process variables such as temperature and pressure. For example, process state or variable estimation may enable a user to determine if the final output of a particular batch process will be acceptable. If it is estimated that the final product output will be below acceptable standards the batch process may be, for example, immediately discontinued. Alternatively, the batch process may be extended beyond the expected time required for the batch process so that the product output will be acceptable.
It is often very difficult, time consuming, and/or expensive, however, to accurately estimate a future state of a batch process. Thus, in one typical approach, a batch process operator may record process conditions of a successful batch process. Then, in subsequent batch processes, the operator may try to precisely maintain batch process conditions close to those of the known successful batch process. In this approach, it is assumed that the final batch process state should be close to that of the known successful batch process if the batch process conditions are maintained close to that of the known successful batch process. Other unmeasured conditions or conditions that cannot be precisely controlled, however, may affect the final batch process state. Therefore, even if many batch process conditions are precisely maintained, the final result of the batch process may vary from that of the known successful batch process.
In another typical approach, a mathematical equation (i.e., a parametric model) may be developed to estimate a rate of reaction of a process, where the equation is a function of measured process conditions. The equation can then be integrated to generate an estimate of the current state of the batch process. Development of such an equation that takes into account many process conditions, however, is usually extremely difficult. Therefore, the developed equation is simplified by making various assumptions, resulting in an equation that provides only a rough approximation of the rate of reaction. Accordingly, any estimate of the current state of the batch process based on such an equation provides only a rough approximation of the current state of the batch process.